Abstract P071: How to Get a Better Night’s Sleep: Be Active and Reduce Sedentary Behaviour
Notice bibliographique
Résumé
Background: Approximately 40% of the population reports sleep problems such as poor quality sleep and insufficient sleep duration. Physical activity (PA) can help improve sleep, but data on whether PA intensity or duration is most strongly associated with sleep are lacking. In addition, given that sedentary behaviour (e.g., TV, computer use) is distinct from physical inactivity, the association between sedentary behaviour and sleep in young adults needs to be characterized. Objective: To describe the relationships between sleep quality and sleep duration and (1) frequency and duration of light, moderate, and vigorous PA, and (2) different types of sedentary behaviours (TV, computer, reading) in young adults. Methods: Self-report data for 658 participants were from the 22nd wave of the Nicotine Dependence in Teens (NDIT) cohort study (mean age=24.0 years, 46% male [300 of 658]). PA measures assessed frequency (number of days) and minutes of light, moderate and vigorous PA in the past week. Sedentary measures assessed number of hours spent reading, watching TV, and using the computer per day. Sleep measures included (1) the Pittsburgh Sleep Quality Index (PSQI) which assessed seven dimensions of sleep (daytime dysfunction, disturbances, duration, efficiency, latency, quality, use of sleeping medications), (2) general sleep quality, and (3) sleep duration in the past month. General sleep quality and sleep duration were two separate additional measures distinct from similar PSQI items (r=0.73 between general sleep quality and PSQI score; r=0.69 between sleep duration and PSQI score). Data were analyzed using multiple linear regression. Due to evidence of non-normality the PSQI score was log-transformed. Results: Controlling for age, sex, and maternal education, each additional day of light or vigorous PA was associated with 3 minutes less sleep per night (p<0.05). Each additional 10 minutes of moderate PA was associated with greater general sleep quality (β=0.004, p=0.04). TV was associated with a poorer PSQI score (β=0.01, p<0.05) and each additional hour of reading was associated with 2 minutes less sleep per night (p=0.04). Computer use was associated with a poorer PSQI score (β=0.02, p=0.005) and poorer sleep quality (β=-0.02, p=0.05). Results were similar when sedentary and PA measures were included in the same model. The inclusion of body mass index, self-rated mental and general health, and stress did not affect the results and were omitted from the final models. Conclusion: PA and sedentary behaviours are independently associated with sleep duration and quality. Sedentary behaviours are associated with poorer sleep duration and quality. In contrast, PA frequency may decrease sleep duration while PA duration may improve sleep quality. Clinicians who treat sleep problems in young adults may need to take PA and sedentary behavior into account in treatment plans.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,013 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».